Abstract
Attention is considered a sufficient condition for transforming input into absorption in the field of second language acquisition and is a major cognitive factor influencing second language learning. The temporal characteristics of attentional shift are a more accurate reflection of second language learners’ thinking processes. Based on this, this study uses deep learning techniques and VR technology to explore the attentional patterns of the second language (English) learners when processing online tasks. The experiments show that the linear attentional control model of young second language learners is closely related to their online task performance, which can visually explain the effect of their linear attentional control on online task completion. The model also has a high regression/prediction accuracy.
Highlights
Cognitive science provides the mechanisms and processes of intelligent activities such as perception and thinking for the study of deep learning in artificial intelligence [1]. e development of cognitive science has advanced deep learning in artificial intelligence by integrating it with a variety of disciplines to analyse and solve problems from different perspectives [2]
Language learning based on deep learning is language learning aided by artificial intelligence devices and can intelligently help people to complete communicative tasks and achieve the social function of interacting with people, their knowledge, and their environment [3]. ere are many intelligent devices that are closely linked to language learning, and they can be divided into three main categories: robots, specialist software, and integrated platforms. e main types of intelligent language devices are Xunfei translators, lip recognition robots, chariots (Chatterbot), Dasai intelligent educational robots, and Xiaobu English educational companion robots
Professional software includes Google Translator, Kingsoft, and Lingoes Translator, e-learning platforms include Library Genesis and Goodreads, Moodle, Black-board, Sakai, and SuperStar Pan-Asia [4]. ese three types of intelligent devices are collectively known as artificial intelligent language learning (AILL), and the difference lies in their different levels of intelligence
Summary
Cognitive science provides the mechanisms and processes of intelligent activities such as perception and thinking for the study of deep learning in artificial intelligence [1]. e development of cognitive science has advanced deep learning in artificial intelligence by integrating it with a variety of disciplines to analyse and solve problems from different perspectives [2]. Cognitive science provides the mechanisms and processes of intelligent activities such as perception and thinking for the study of deep learning in artificial intelligence [1]. E development of cognitive science has advanced deep learning in artificial intelligence by integrating it with a variety of disciplines to analyse and solve problems from different perspectives [2]. Language learning based on deep learning is language learning aided by artificial intelligence devices and can intelligently help people to complete communicative tasks and achieve the social function of interacting with people, their knowledge, and their environment [3]. Ere are many intelligent devices that are closely linked to language learning, and they can be divided into three main categories: robots, specialist software, and integrated platforms. This paper, based on an introduction to AI and language learning, explores the cognitive basis of intelligent language learning, i.e., extended cognition, and points out its new implications for second language acquisition [7]
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